Opposites Attract: Complementary Phenotype Selection for Crossover in Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{dolin:ppsn2002:pp142,
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author = "Brad Dolin and Maribel Garcia Arenas and
Juan J. Merelo Guervos",
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title = "Opposites Attract: Complementary Phenotype Selection
for Crossover in Genetic Programming",
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booktitle = "Parallel Problem Solving from Nature - PPSN VII",
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address = "Granada, Spain",
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month = "7-11 " # sep,
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pages = "142--152",
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year = "2002",
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editor = "Juan J. Merelo-Guervos and Panagiotis Adamidis and
Hans-Georg Beyer and Jose-Luis Fernandez-Villacanas and
Hans-Paul Schwefel",
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number = "2439",
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series = "Lecture Notes in Computer Science, LNCS",
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publisher = "Springer-Verlag",
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keywords = "genetic algorithms, genetic programming, Evolutionary
computing, Selection",
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ISBN = "3-540-44139-5",
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DOI = "doi:10.1007/3-540-45712-7_14",
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abstract = "Standard crossover in genetic programming (GP) selects
two parents independently, based on fitness, and swaps
randomly chosen portions of genetic material
(subtrees). The mechanism by which the crossover
operator achieves success in GP, and even whether
crossover does in fact exhibit relative success
compared to other operators such as mutation, is
anything but clear [14]. An intuitive explanation for
successful crossover would be that the operator
produces fit offspring by combining the 'strengths' of
each parent. However, standard selection schemes choose
each parent independently of the other, and with regard
to overall fitness rather than more specific phenotypic
traits. We present an algorithm for choosing parents
which have complementary performance on a set of
fitness cases, with an eye toward enabling the
crossover operator to produce offspring which combine
the distinct strengths of each parent. We test
Complementary Phenotype Selection in three genetic
programming domains: Boolean 6-Multiplexer, Intertwined
Spirals Classification, and Sunspot Prediction. We
demonstrate significant performance gains over the
control methods in all of them and present a
preliminary analysis of these results.",
- }
Genetic Programming entries for
Brad Dolin
Maribel Garcia Arenas
Juan Julian Merelo
Citations